Statistical Analysis with R For Dummies, 2nd Edition

Index

A

• a posteriori tests, 236–237
• a priori tests, 232–234
• abs() function, 179, 203
• adding graph features, 57–59
• adjusting R-squared, 326–327
• aes() function, 66–67, 70–71
• aesthetic mapping, 66, 127
• alpha (α), 172–175
• alternative hypotheses, 15, 172
• analysis, for logistic regression, 406–409
• analysis of covariance (ANCOVA), general linear model (GLM) and, 302–308
• analysis of variance (ANOVA)
  • about, 43, 229
  • in R, 230–237
  • regression and, 298–302
  • two-way, 251–253
• annotate() function, 196
• anova() function, 305, 307, 354
• aov() function, 43, 230, 298
• applying central limit theorem, 199–200
• argument, 26
• as.character() function, 62–63
• assignment operator, 22
• attach() function, 83
• average
  • mean, 79–87
  • median, 87–89
  • mode, 89–90
  • squared deviations, 92–95

B

• backslash, 22
• bar graphs
  • about, 51–52
  • in base R graphics, 59–60
  • in ggplot2, 69–70
  • for two-sample hypothesis tests, 210–211
• barplot() function, 59–60
• base, 336
• base R graphics
  • about, 56
  • adding features, 57–59
  • bar graphs, 59–60
  • box plots, 65
  • histograms, 56–57
  • pie graphs, 61
  • plotting chi-square in, 194–195
  • plotting t in, 183–185
  • scatterplots, 61–65
• bell curve, 133–137
• beta (β), 172–175
• bimodal, 89
• bin, 68
• binomial distribution
  • about, 372–373
  • hypothesis testing with, 376–378
  • negative, 375–376
  • in R, 373–375
• binomial experiment, 372
• binom.test() function, 377, 378, 380
• books, online, 430–432
• box plots
  • about, 53–54
  • in base R graphics, 65
  • in ggplot2, 75–77
  • for two-sample hypothesis tests, 208–210
• box-and-whiskers plot, ...